KR101284892B1 - An intelligent prevention method of internet addiction based on user task inference - Google Patents

Abstract

PURPOSE: A smart internet addiction prevention method capable of expecting a user's Internet using purpose allows a user to use a set of web sites which have been approved based on Internet-related work information and cuts off the user's access to web sites with low relevance by comparing the current work of the user with a preset work description. CONSTITUTION: An Internet use purpose collection module identifies a user's Internet using purpose online and stores the purpose in a database (S10). When the user gets access to the Internet, an Internet using behavior monitoring module monitors the user's activities on the Internet using an agent and stores the user's Internet-related working log files in a local computer or a smart device with the user's consent (S30). A keyword extraction and using purpose matching module analyzes the key words of sub menus of the web sites in the working log files, matches the key words with using purpose categories, and stores the results in a user behavior database (S40). [Reference numerals] (10) Identify a user's purpose in using the Internet; (20) Monitor the user's behaviors on the Internet; (30) Extract the user's major keywords and match the words with the user's Internet use purpose; (40) Learn about the user's work relevance between the purpose and the behaviors; (50) Determine the work relevance regarding the user's behavior on the Internet; (60) Allow or deny the user's Internet use; (AA) Start; (BB) Internet-related work log file; (CC) Purpose of use profile database; (DD) Work relevance rules database; (EE) User behavior database; (FF) Purpose of use profile database; (GG) User behavior database; (HH) Add a new rule; (II) Is there a relevance rule?; (JJ) End

Description

An intelligent prevention method of internet addiction based on user task inference}

The present invention relates to an internet addiction prevention method for preventing internet addiction, and more particularly, to deduce the relationship between the user's registered internet usage range and purpose in the field of internet time limit and harmful information blocking, irrespective of the user's work. An Internet addiction prevention method through a user task inference to prevent excessive use of the Internet.

In the age of one computer, most people use their computers to access the Internet. Such general Internet use has improved the quality of life and made daily life much more convenient.

The purpose of using the Internet is expanding to a variety of fields ranging from information acquisition activities such as e-mail confirmation, web surfing, news / information search, and leisure / entertainment activities such as games, video downloads, and novel network services (SNS). The Internet has many functions, but due to the nature of the media, Internet addiction has become an addiction that consumes more time than expected.

In other words, Internet addicts are increasing rapidly by using unlimited chat, games, pornography, etc. In particular, most internet addicts do not realize that they are addicts, but the problem is serious. Such an Internet addiction causes social opportunity loss of opportunity, not merely a waste of time for each individual.

Therefore, there is a need for effective ways to prevent Internet addiction. In particular, for the young adults, the compulsory method is not effective, so a method of voluntarily preventing Internet addiction is necessary. In order to fundamentally get rid of Internet addiction, it is important for users to be naturally aware of Internet addiction. For example, informing the end time of Internet use or forcibly restricting the use of the Internet, the user's rejection is not only large, but also does not work for adults such as young adults.

Accordingly, as a related art developed to prevent Internet addiction, "Internet addiction diagnosis apparatus, treatment plan inference device and treatment system using expert system" of Patent Publication No. 2010-0137966 is published in the Patent Publication.

Patent Publication No. 2010-0137966, "Internet Addiction Diagnosis Device, Treatment Inference Device and Treatment System Using Expert System," uses a knowledge editor and data mining technique that converts a professional treatment knowledge base into a rule-based treatment knowledge base. Automatically treat Internet addiction by inferring internet addiction treatment using expert system by using data mining based diagnosis unit that judges user's internet addiction, knowledge base including rule based treatment knowledge base and knowledge base. The automation of diagnosis and treatment is realized through expert systems using customized treatment knowledge.

However, since the Patent Publication No. 2010-0137966 is a technology for treating Internet addicts, there is a problem that it is not possible to prevent Internet addiction in advance.

In addition, a conventional technology discloses a "connection blocking device for preventing Internet addiction" of Korean Patent Publication No. 2011-0020970.

Patent Publication No. 2011-0020970 "connection blocking device for preventing Internet addiction" is a power input unit; An internet input unit connected to a router or a modem to receive internet data from the outside; An internet output unit connected to a computer to output input internet data input to the internet input unit; A switch unit for setting a usage time period for connecting to the Internet, and setting a program cycle of an on / off time within the usage time time for connecting to the Internet; A microcomputer controlling the use of the Internet continuously through a repetitive method of blocking or reconnecting Internet access according to a period of time set by the switch unit; A relay unit for physically or electrically turning on / off a connection between the router or the modem and the computer by switching a connection line between the Internet input unit and the Internet output unit according to the control signal of the microcomputer; A clock display unit displaying a current time; A usable display unit which displays a current Internet usage state used by the microcomputer; An internet phone input unit connected to the router or modem to connect an internet phone from the outside; And an Internet telephone output unit that is always connected to an internal Internet telephone regardless of internet on / off of the relay unit under the control of the microcomputer, and determines a usage time limit for accessing the Internet, and accessing the Internet. It is to make continuous internet use impossible through the repetitive method of blocking or reconnecting internet access according to the period of program set time within the limit time.

On the other hand, the conventional Internet addiction prevention method as shown in Figure 1 is the Internet blocking rule registration step (S1 step); A commercial internet access step (step S2); A rule determination step (step S3) of determining whether or not the Internet blocking rule registration step (S1 step) matches the rule registered; According to the determination result of the rule determination step (S3 step), it was a simple method comprising an internet blocking and allowing step (S4 step) of blocking or allowing the use of the Internet.

However, in addition to the Patent Publication No. 2011-0020970, the conventional Internet addiction prevention method of FIG. 1 is provided with commercial software as a program that provides functions such as time management of Internet users, prevention of game addiction, and prevention of harmful substances. It is applied in the same way, and there is a limit that the parent sets the use time or the blocking site without the user's consent mainly for the purpose of suppressing the internet use for the teenagers.

The present invention has been invented to solve various defects and problems caused by the conventional Internet addiction prevention technology in view of the above circumstances, the purpose of the user in advance, instead of the time limit or harmful information judgment criteria registered by the administrator Based on the registered internet-related information, the system allows sites that are pre-approved, and if it is determined that the site is less relevant through the step of comparing the association between the registered work scope and the current work, it is blocked. It is to provide intelligent internet addiction prevention method through user's work inference that can contribute to company's productivity.

Another object of the present invention is to provide an intelligent Internet addiction prevention method through inference of user work that extends the application to all Internet users while reducing excessive Internet use beyond the intended level.

Another object of the present invention is to reduce the cost through efficient management of information resources by limiting unnecessary use of the Internet at home and at work, the individual user will be used as a site that meets the purpose of the Internet registered by the user, excessive use is It is to provide an intelligent Internet addiction prevention method through the user's work inference that can increase the physical and mental health resulting from the establishment of sound Internet usage habits.

Another object of the present invention is applicable to a portable computing device, such as a smart phone or a smart pad as well as an office environment, intelligent internet addiction prevention method through the user task inference that can be applied to various areas that need user work recognition in the ubiquitous environment To provide.

The intelligent Internet addiction prevention method through the inference of the user's work to achieve the above object is the Internet use purpose collection module 10, the Internet use purpose registration step of collecting the user's Internet use purpose online and storing it in the database (step S10) Wow; A user access step (S20 step) of the user accessing the Internet; Observing the internet usage behavior step of observing the user's internet usage behavior using the agent as the internet usage behavior observation module 20 and storing the user's internet work log file in the computer or smart device used with the user's consent ( Step S30); The keyword extraction and usage matching module 30 analyzes the keywords of the sub-click menu of the website in the internet work log file and matches them to one of the usage purpose categories, and extracts and uses the keywords to store the result in the user behavior database. A matching step (step S40); The task association learning module between the Internet usage purpose and the user behavior learning module 40 analyzes the information stored in the user profile database and the user behavior database, which is constructed for each user, using the association analysis technique, which is one of the data mining techniques, for each user. A work relevance learning step (S50 step) of learning work relevance of the Internet use behavior; The work relevance determination module 50 uses the Internet to determine work relevance by matching the work relevance rules for each user stored in the work relevance rule database with the user's Internet use information Up and user use behavior detection information Ub. A task association determination step for the action (step S60); It is characterized in that the Internet use blocking or allowing module 60 determines the relationship between the user's use of the Internet and the operation and the Internet use blocking or allowing step (step S70) to block or allow Internet use according to the result. .

In the present invention, instead of the time limit or harmful information judgment criteria registered by the administrator, the site is allowed in advance in the system based on the Internet-related work information registered in advance by the user, and the previously registered work scope and the work currently being performed By comparing the relevance of the site, if the site is judged to be less relevant, it can block individual and corporate productivity, and extend the application to all Internet users, while avoiding excessive use of the Internet. Reduces costs through efficient management of information resources by limiting unnecessary Internet use at home and at work, and enables individual users to focus on sites that meet the purpose of their registered Internet use and to prevent overuse. Internet use Not only can it increase the physical and mental health of habits, but it can be applied not only to the office environment but also to portable computing devices such as smartphones and smart pads, so that it can be applied to various areas that require user work recognition in the ubiquitous environment. have.

1 is a flow chart for executing a conventional method for preventing internet addiction,
2 is a conceptual diagram of a method for preventing intelligent internet addiction through inference of user operation of the present invention;
3 is a flow chart for executing the intelligent Internet addiction prevention method through the user task inference of the present invention.

Hereinafter, with reference to the accompanying drawings will be described in detail a preferred embodiment of the intelligent Internet addiction prevention method through the user task inference of the present invention.

2 is a conceptual diagram of an intelligent internet addiction prevention method through the user's work inference of the present invention, Figure 3 is a flow chart for executing the intelligent internet addiction prevention method through the user's work inference of the present invention, intelligent internet addiction prevention through the user's work inference of the present invention The system for executing the method includes: an Internet usage collection module 10 which collects the Internet usage targets online and stores them in a database; An internet usage behavior observing module 20 for observing a user's internet usage behavior using an agent and storing the user's internet work log file in a computer or a smart device used with the user's consent; A keyword extraction and usage matching module 30 for analyzing keywords in the lower click menu of the website in the internet work log file and matching the keywords with one of the usage purpose categories, and storing the result in the user behavior database; Internet usage purpose and use behavior that learns the work association of Internet use behavior by user by analyzing the information stored in the usage profile database and user behavior database, which is confused by user, using the association analysis technique, one of data mining techniques. Task association learning module 40 between; Work association determination module for Internet use behavior that matches the user's Internet usage information (Up) and user usage behavior detection information (Ub) with each user's task association rules stored in the task association rule database to determine the work association. 50) and; It is composed of the Internet use blocking or allowing module 60 to determine the relationship between the user's use of the Internet and work and block or allow the use of the Internet according to the result.

In addition, the intelligent Internet addiction prevention method through the user task inference according to the present invention, the Internet use purpose collection module 10, the Internet use purpose registration step of collecting the user's Internet use purpose online and storing it in a database (step S10); A user access step (S20 step) of the user accessing the Internet; Observing the internet usage behavior step of observing the user's internet usage behavior using the agent as the internet usage behavior observation module 20 and storing the user's internet work log file in the computer or smart device used with the user's consent ( Step S30); The keyword extraction and usage matching module 30 analyzes the keywords of the sub-click menu of the website in the internet work log file and matches them to one of the usage purpose categories, and extracts and uses the keywords that store the result in the user behavior database. An objective matching step (step S40); Work association between internet use purpose and user behavior Learning module 40 analyzes information stored in user profile database and user behavior database constructed by user through association analysis, one of data mining techniques. A work association learning step (S50 step) of learning work associations of Internet use behaviors; The job relevance determination module 50 determines the job relevance by matching the user relevance rule (User) and the user use behavior detection information (Ub) with the user relevance rule stored in the job relevance rule database. A task association determination step (S60) for the use behavior; The Internet use blocking or allowing module 60 is configured to determine the relationship between the user's use of the Internet and the operation and block or allow the use of the Internet according to the result (S70).

Example

The intelligent Internet addiction prevention method through the user's work inference of the present invention made as described above will be described in detail with reference to the following examples.

In the step of registering the purpose of using the Internet (step S10), the purpose of using the Internet is collected online and stored in a database. The purpose of use may be defined as an e-mail, information search, shopping, music, video, game, adult content, social networking service (SNS) activities such as chat or mini homepage, Facebook, and the like. The user can check the application directly (duplicate checks possible), and the result is stored in the application profile database. At this time, the site usage time limit value (Tmax_p) for each purpose of Internet use was also stored in this application profile database.

Subsequently, in the user accessing step (S20), the user accesses the Internet, and in the internet using behavior monitoring step (S30), the user uses the agent as the internet using behavior monitoring module 20 to perform the user's internet using behavior. We observed and saved the user's Internet work log file from the computer or smart device that he used with his or her consent.

Subsequently, in the keyword extraction and usage matching step (step S40), the keyword extraction and usage matching module 30 analyzes the keywords of the sub-click menu of the website in the internet work log file and matches one of the usage purpose categories. ， These results are stored in the user behavior database.

Here, as a keyword, all the nouns included in the web page name and address (URL) viewed by the user are extracted, and not only one but also two or more keywords can be extracted, and the similarity between the extracted keyword and the usage category It can be calculated using the similarity function of a general-purpose structural vocabulary database (such as WordNet).

Then, in the task association learning step (S50), the information related to the usage profile database and user behavior database constructed for each user by the task association learning module 40 between the Internet usage purpose and the user behavior is used as one of data mining techniques. We analyzed the work-relatedness of Internet use behavior by user by analyzing it with the Associative Analysis technique. When the learned association rule comes out, it checks whether the purpose of use matches the category of the use behavior and assigns the task association determination value of '0' or '1' to the rule as follows. In the rules below, Up is user use purpose of the Internet (use_purpose), and Ub represents user use behavior (use_behavior) information.

Upi: User's Internet usage category (i = 1, ..., category number)

      The category designated by the user for use in advance is '1'.

      Category is set to '0'.

Ubi is the user's Internet usage category (0 = 1, ..., category number)

      The category you are currently using is "1", all other categories

      Log is set to '0'.

Rule (Upi, Ubi) = determined by '0' or '1' as the logical product of Upi, Ubi

D_Rule (Up, Ub) = '0' or '1' as the nominal sum of all Rule (Upi, Ubi) items

                 Determined by

In the following case, Rule (Upi, Ubi) is the same as the bottom of Table 1, and D_Rule (Up, Ub) becomes '1'.

Category   C1   C2   C3   C4   C5   C6   C7   C8   C9   C10    Upi   One   0   0   0   One   0   0   0   0   One    Ubi   One   0   0   0   0   0   0   0   0   0 Rule (Upi, Ubi)   One   0   0   0   0   0   0   0   0   0

D_Rule (Up, Ub), which is a result including the weight of '0' or '1' for each learning rule, is stored in the work relevance rule database. This information is used when a user actually connects to an Internet site to determine job association.

Then, in the task association determination step (S60) for the Internet use behavior, the task association determination module 50 carries the user's Internet usage purpose information Up and the user usage behavior detection information Ub to the task association rule database. If there is a matching rule by matching the stored task association rule for each user, '1' is allowed and '0' is blocked using D_ Rule (Up, Ub) which is archived decision information. If no matching rule is found, it is added as a new rule to the task association rule database. At this time, the task association judgment value of '0' or '1' is checked by checking whether the purpose of use and the category of the behavior are matched. Assigned to the rules added in the manner performed in the learning module, it was determined whether the user is allowed to use.

Subsequently, in the blocking or allowing step of using the Internet (step S70), the Internet using blocking or allowing module 60 determines the relationship between the user's use of the Internet and the job and blocks or allows the use of the Internet according to the result. At this time, regardless of whether or not work-related activity is measured by the user's Internet use time (Tb), even if the work-related activity exceeds the maximum daily use time (Tmax_p) preset for each purpose of use, the Internet is suspended and the set time is Internet addiction was prevented by restricting access back only if increased (user_addup_time = = true). If it was determined to be unrelated to work, the Internet was immediately blocked regardless of the usage time limit. This process can be expressed as pseudo code as below.

if (D_Rule (Up, Ub) == 0)

then Stop_Internet_Use // Block the Internet

else if (Tb> Tmax_P)

       then {Stop_Internet_Use // Block the Internet

      if (user_addup_time == true)

      then Allow_Internet_Use} // Allow Internet Access

       else Allow_Internet_Use // Allow Internet Access

While the present invention has been described as a preferred embodiment, the present invention is not limited thereto, and various modifications can be made without departing from the spirit of the invention.

10: collection module for the purpose of using the Internet 20: observation module for the use of the Internet
30: keyword extraction and purpose matching module
40: Learning module of task association between purpose of internet use and behavior
50: task association determination module 60: Internet use blocking or allowing module

Claims (6)

An Internet usage purpose registration step (S10 step) of collecting the Internet usage purpose for the user online using the Internet usage purpose collection module 10 and storing it in a database; A user access step (S20 step) of the user accessing the Internet; Observing the internet usage behavior step of observing the user's internet usage behavior using the agent as the internet usage behavior observation module 20 and storing the user's internet work log file in the computer or smart device used with the user's consent ( Step S30); The keyword extraction and usage matching module 30 analyzes the keywords of the sub-click menu of the website in the internet work log file and matches them to one of the usage purpose categories, and extracts and uses the keywords that store the result in the user behavior database. An objective matching step (step S40); Work association between internet use purpose and user behavior Learning module 40 analyzes information stored in user profile database and user behavior database constructed by user through association analysis, one of data mining techniques. A work association learning step (S50 step) of learning work associations of Internet use behaviors; The job relevance determination module 50 determines the job relevance by matching the user relevance rule (User) and the user use behavior detection information (Ub) with the user relevance rule stored in the job relevance rule database. A task association determination step (S60) for the use behavior; Internet use blocking or allowing module 60 determines the relationship between the user's use of the Internet and the operation and infers the user's work consisting of an internet use blocking or allowing step (step S70) to block or allow Internet use according to the result. How to prevent intelligent internet addiction through The method of claim 1, wherein the purpose of using the Internet in the step of registering the purpose of using the Internet (step S10) is a social networking service such as e-mail, information search, shopping, music, video, games, adult content, chat, mini homepage, Facebook ( Intelligent Internet addiction prevention method through the user task inference, characterized in that any one of the SNS) activity. 2. The method of claim 1, wherein the keyword in the keyword extraction and use purpose matching step (step S40) is a noun included in a web page name and address read by the user. Way. The method according to claim 1, wherein when the association rule learned in the task association learning step (step S50) comes out, the task association determination value of '0' or '1' is determined by checking whether the purpose of use and the category of the behavior are matched as follows. Intelligent Internet addiction prevention method based on user task inference, characterized in that specified in the rule.
Upi: User's Internet usage category (i = 1, ..., category number)
The category designated by the user for use in advance is '1'.
Category is set to '0'.
Ubi is the user's Internet usage category (0 = 1, ..., category number)
The category you are currently using is "1", all other categories
Lee is set to '0'.
Rule (Upi, Ubi) = determined by '0' or '1' as the logical product of Upi, Ubi
D_Rule (Up, Ub) = '0' or '1' as the nominal sum of all Rule (Upi, Ubi) items
Judging by.
Here, Up is information on the use of the user (use_purpose), and Ub is information on the use of the user (use_behavior). According to claim 1, In the step of blocking or allowing the use of the Internet (step S70), regardless of whether or not the activity irrelevant activity by measuring the user's Internet use time (Tb), even if the work-related activities, the maximum daily use time set in advance for each purpose of use If (Tmax_p) is exceeded, intelligent internet addiction through user task inference, which prevents internet addiction by suspending internet use and restricting access to only when setting time is increased (user_addup_time = = true) Prevention method. 6. The method of claim 5, wherein if it is determined to be unrelated to work, the Internet is immediately blocked regardless of the usage time limit.

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